activity
20232026
most citedQwen3-VL Technical Report

16 citations · 17 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CV2026

Beacon: Knowing When and How to Perform Agentic Visual Reasoning

Qixun Wang, Yang Shi, Letian Cheng +11

The fundamental goal of agentic visual reasoning is to improve the success rate of multimodal large language models (MLLMs) on complex tasks. We rethink agentic visual reasoning th…

cs.CV2025★ 16 cited

Qwen3-VL Technical Report

Shuai Bai, Yuxuan Cai, Ruizhe Chen +61

We introduce Qwen3-VL, the most capable vision-language model in the Qwen series to date, achieving superior performance across a broad range of multimodal benchmarks. It natively…

cs.CL2025

BiasFreeBench: a Benchmark for Mitigating Bias in Large Language Model Responses

Xin Xu, Xunzhi He, Churan Zhi +3

Existing studies on bias mitigation methods for large language models (LLMs) use diverse baselines and metrics to evaluate debiasing performance, leading to inconsistent comparison…

cs.AI2025

RealUnify: Do Unified Models Truly Benefit from Unification? A Comprehensive Benchmark

Yang Shi, Yuhao Dong, Yue Ding +22

The integration of visual understanding and generation into unified multimodal models represents a significant stride toward general-purpose AI. However, a fundamental question rem…

cs.CL2025

BiasFilter: An Inference-Time Debiasing Framework for Large Language Models

Xiaoqing Cheng, Ruizhe Chen, Hongying Zan +2

Mitigating social bias in large language models (LLMs) has become an increasingly important research objective. However, existing debiasing methods often incur high human and compu…

cs.CL2025

Evolutionary Guided Decoding: Iterative Value Refinement for LLMs

Zhenhua Liu, Lijun Li, Ruizhe Chen +5

While guided decoding, especially value-guided methods, has emerged as a cost-effective alternative for controlling language model outputs without re-training models, its effective…

stat.AP2025★ 1 cited

Performance Evaluation of Large Language Models in Statistical Programming

Xinyi Song, Kexin Xie, Lina Lee +10

The programming capabilities of large language models (LLMs) have revolutionized automatic code generation and opened new avenues for automatic statistical analysis. However, the v…

cs.CL2023

QTSumm: Query-Focused Summarization over Tabular Data

Yilun Zhao, Zhenting Qi, Linyong Nan +9

People primarily consult tables to conduct data analysis or answer specific questions. Text generation systems that can provide accurate table summaries tailored to users' informat…